A QTL of eggplant shapes the rhizosphere bacterial community, co-responsible for resistance to bacterial wilt

Abstract Resistant crop cultivars can recruit beneficial rhizobacteria to resist disease. However, whether this recruitment is regulated by quantitative trait loci (QTL) is unclear. The role of QTL in recruiting specific bacteria against bacterial wilt (BW) is an important question of practical significance to disease management. Here, to identify QTL controlling BW resistance, Super-BSA was performed in F2 plants derived from resistant eggplant cultivar R06112 × susceptible cultivar S55193. The QTL was narrowed down through BC1F1-BC3F1 individuals by wilting symptoms and KASP markers. Rhizosphere bacterial composition of R06112, S55193, and resistant individuals EB158 (with the QTL) and susceptible individuals EB327 (without QTL) from BC2F1 generation were assessed by Illumina sequencing-based analysis, and the activation of plant immunity by the bacterial isolates was analyzed. Evidence showed that BW-resistant is controlled by one QTL located at the 270 kb region on chromosome 10, namely EBWR10, and nsLTPs as candidate genes confirmed by RNA-Seq. EBWR10 has a significant effect on rhizobacteria composition and significantly recruits Bacillus. pp. A SynCom of three isolated Bacillus. pp trains significantly reduced the disease incidence, changed activities of CAT, PPO, and PAL and concentration of NO, H2O2, and O2−, activated SA and JA signaling-dependent ISR, and displayed immune activation against Ralstonia solanacearum in eggplant. Our findings demonstrate for the first time that the QTL can recruit beneficial rhizobacteria, which jointly promote the suppression of BW. This method charts a path to develop the QTL in resistant cultivar-driven probiotics to ameliorate plant diseases.


Introduction
Bacterial wilt (BW) caused by Ralstonia solanacearum infects about 250 plant species, especially plants from the Solanaceae family, which is considered a major problem in humid tropical and subtropical regions worldwide [1,2].To date, various managements have been explored for the control of BW, including breeding resistant cultivars, chemical and biological controls, and soil management, but the control of this disease at a desired level through a sustainable and eco-friendly way is still awaited [2][3][4].Breeding-resistant cultivars are still the most logical, economical, and environmental solution for suppressing BW epidemics [2,3].Plant resistance to BW is very complex and controlled by QTLs.Genetic analysis using Arabidopsis accession Landsberg erecta (Ler) × Col-0 recombinant inbred lines suggested that R. solanacearum resistance is controlled by three loci, namely QRS1, QRS2, and QRS3 [5].Several major QTLs on chromosomes 6, 7, and 10 in Solanum lycopersicum var.cerasiforme cultivar L285 [6,7] and chromosomes 3, 6, 8, 10, and 11 in S. lycopersicum cultivar 'Hawaii 7996' associated with BW resistance were identified [8][9][10][11].Previous studies have suggested that the resistance of eggplant to BW is monogenic, while studies reported it as polygenic [12].A major gene, ERs1 conferring resistance to R. solanacearum was identified by Solanum melongena MM738 (susceptible) × AG91-25 (resistant) recombinant inbred lines located in chromosome 9 and named EBWR9.Two other QTLs were identified on chromosomes 2 and 5, named EBWR2 and EBWR5, respectively [13][14][15].Although the main emphasis of BW research is on breeding resistant cultivars has been a challenge for many years [2].Due to the breeding, cultivars resistant to BW have been restrained by polygenic inheritance, and sometimes the connection between resistance with horticultural undesirable traits related to the wild species (linkage drag) [7,16].There is still a need for cultivars with stable resistance, and the genetics of bacterial wilt resistance is still unclear.
Rhizosphere microecological balance may contribute to determining the resistance to BW [17].Some bacterial taxa have been designated as plant growth-promoting rhizobacteria for BW management [18,19].The composition and function of root microbiomes are highly dependent on the plant genotypes and phenotypic traits and the environment in which they live [20,21].Plants select microorganisms to colonize in their rhizosphere, and this process is heritable across plant cultivars [22,23].The research of Poudel et al. [24] highlighted the inf luence of different rootstock varieties on the composition of the bacteria community in the tomato rhizosphere which proves the potential for selecting bacterial taxa by plant genotype.Studies have shown the inf luence of genotype on plant-associated microbiome composition in crop varieties and their wild relatives, and genespecific mutations [21,25].Hence, the identification of genes related to specific plant-associated microbial recruitment is the critical step to developing new methods of crop breeding that are able to recruit beneficial microorganisms that support crop health [21], yet the implication of BW resistance genes on rhizosphere microbiome function has been relatively unexplored.
BW of eggplant (S. melongena L.) is a major economically destructive disease, causing the yield reduced from 11.67% to 96.67% and even recorded up to 100% loss in humid and congenial climatic conditions [2,15,26].There are few resources for resistance to BW in eggplants available in nature [12].The eggplant-resistant cultivar R06112 with good commercial properties and a high yield and wide adaptation was used in this study, which could be introgressed into commercial cultivars.The mechanism of BW resistance in eggplant remains scant, restricting resistance breeding and disease management.Therefore, this study aimed to (i) locate the BW resistance locus of eggplant R06112; (ii) decipher the rhizosphere bacterial communities driven by the QTL; (iii) isolate trains significantly recruited by the QTL with strong biocontrol potentials against R. solanacearum from rhizosphere soil; and (iv) evaluate BW resistance mechanisms of SynCom composed of isolated trains against R. solanacearum.

BW resistance inheritance in the eggplant R06112
Chi-squared (χ 2 ) analysis was carried out to test the phenotypic data for goodness-of-fit to Mendelian segregation ratios.Two clear-cut BW-response phenotypes, asymptomatic or death were counted in the F 2 population during 21 dpi.Among 320 F 2 plants, 94 showed BW susceptibility, and 226 showed BW resistance, with a 3:1 segregation between resistant and susceptible plants (χ 2 = 3.27, P = 0.07).All F 1 plants showed BW resistance.The segregating population BC 1 P s and BC 1 P r populations with 1:1 and 1:0 segregation ratios between resistant and susceptible plants (Table S2, see online supplementary material).The results suggested that resistance to R. solanacearum in R06112 was controlled by a single dominant gene.

A monogenic resistance in R06112 with one QTL
We obtained 60.49Gb of clean data from the parents and 56.33 Gb from the two mixed pools, with high quality (89.65% > Q30 > 88.70%) and stable GC content (36.51% > GC > 35.79%).The average sequencing depths for two F 2 pools and parents were 23× and 22×, respectively.In total, 1 712 421 SNPs were identified and after filtering, 201 707 polymorphic SNPs between the resistant and the susceptible DNA bulks were used for association analysis to identify the resistance-related candidate regions in eggplant.A 4.96 Mb region spanning 89.162 and 94.122 Mb on chromosome 10 was identified as the target region associated with BW resistance (Fig. 1A and B).Through the identification of BC 1 F 1 -BC 3 F 1 individuals by KASP markers and disease resistance in the field, the position of BW resistance QTL was located between SNP908 and SNP910, a 270 kb region, which was designated EBWR10 (Fig. 1C and D).Twenty genes were annotated in the region, including four non-specific lipid-transfer protein (nsLTPs) genes.The RNA-Seq analysis indicated that the expression levels of two nsLTPs genes were significantly upregulated in R06112 by R. solanacearum inoculation (Fig. 1E), which was identified as the most likely candidate gene which confers BW resistance in eggplant R06112.Silencing nsLTP reduced eggplant R06112 resistance to BW by Virus-induced gene silencing (VIGS) analysis (Fig. S2, see online supplementary material).

Effect of EBWR10 on community composition of rhizosphere bacteria
The bacterial microbiota associated with R06112, S51193, and the BC 2 P s individual plants with EBWR10 (EB158-94) and without EBWR10 (EB327-77) were evaluated.A total of 1 543 275 highquality sequences with an average of 64 303 reads in each sample were obtained by Illumina high-throughput sequencing, which was binned (N97% identity) into 9747 operational taxonomic units (OTUs).
PCoA analysis suggested that the bacterial community structure of R06112 rhizosphere soil was different from EB158, EB327, and S51193.The bacterial community of EB158 tended to separate from EB327 and S51193.Permutational Multivariate Analysis of Variance (PERMANOVA) showed that the bacterial community structure was significantly different among these sample groups (Fig. 2C).The rhizosphere soils clustered into two groups based on bacterial community composition by UPGMA tree, suggesting that the bacterial community of EB158 and EB327 was more similar to the S51193 (Fig. 2D).Shannon and Chao1 of the rhizospheric bacterial community were significantly higher in EB158, and the Shannon index was significantly higher in EB327 than R06112 and S51193 (Table S3, see online supplementary material).
The relative abundances of Firmicutes and Gemmatimonadetes in the rhizosphere soil of R06112 were significantly higher than that in S51193 and EB327 (P < 0.01).The relative abundances of Actinobacteriota and Chlorof lexi in the rhizosphere soil of the resistant progeny EB158 were significantly higher than that in susceptible parent S51193 and susceptible progeny EB327 (P < 0.01) (Fig. 3).The relative abundance of bacterial orders with significantly different levels is shown in Fig. S4 (see online supplementary material).
The abundance of Bacillus was significantly higher in resistant parent R06112 (with EBWR10) and resistant progeny EB158 (with EBWR10) than in susceptible progeny EB327 (without EBWR10) and susceptible parent S51193 (without EBWR10) (Fig. 4).Relative abundances of Bacillus were 1.61-fold and 1.29-fold higher in the rhizosphere soil of R06112 and EB158 than in S51193, respectively.The relative abundances of Bacillus in the rhizosphere soil of EB327 were similar to that in S51193 (Fig. 4).

Isolation and identification of antagonistic Bacillus strains against R. solanacearum
Among 273 isolated strains, three showed strong antagonism against R. solanacearum GMI1000 on LB medium (Fig. S5

Activation of plant immunity by a synthetic community (SynCom)
The disease incidence and disease index of eggplant inoculation with R. solanacearum were significantly reduced at 7 dpi by SynCom treated (Fig. 5A-C).In addition, SynCom could promote eggplant growth to a certain extent (Fig. 5A).
To evaluate the physiological effects and functional mechanisms of SynCom on BW resistance, we compared changes in activity of phenylalanine ammonialyase (PAL), catalase (CAT), and polyphenol oxidase (PPO), superoxide (O Compared to the control and R. solanacearum treatments, the concentration of JA and SA was significantly increased by SynCom inoculation (Fig. 5D and E).The expression levels of the defense-related marker genes involved in JA and SA signaling in systemic leaves were analysed to identify whether the SynCom activates defense signaling in eggplant.The expression of SA signaling marker genes EDS1, GluA, NPR1, and SGT1 was upregulated by 2.7-, 6.0-, 3.1-fold, and 1.5-fold, respectively, in eggplant treated with SynCom (Fig. 6A).The expression levels of TGA, PAD4, and PR-1a have no significant difference between R. solanacearum and R. solanacearum plus SynCom plants (Fig. S11, see online supplementary material).Compared to control and R. solanacearum treatment, the expression of JA signaling marker gene LoxA upregulated by 12.5-, and 2.1-fold at 48 hpi, respectively, in eggplant treated with SynCom, while the expression of the Pin2 gene declined compared with the control (Fig. 6B).In addition, SA-biosynthetic gene ICS1 was increased in R. solanacearum plus SynCom treatment plants compared to control and R. solanacearum.SA catabolic gene PBS3 was significantly higher in control than in other treatments (Fig. 6A).These results indicate that the SynCom primed SA-and JA-dependent induced systemic resistance (ISR) against R. solanacearum in eggplant.

Discussion
Host resistance and the rhizosphere microecological balance are the most effective and eco-friendly in controlling BW, as are other soil-borne diseases.Depending on the varieties used, resistance to R. solanacearum in eggplant is controlled by one dominant gene, one recessive gene, or recessive polygene [14,[26][27][28].Due to the relation of BW resistance with horticultural undesirable traits related to the wild species, the majority of varieties cannot be used directly for breeding.The resistant cultivar R06112 with good quality and commercial property has tremendous potential for  introgression into commercial cultivars.R. solanacearum resistance in R06112 is controlled by one QTL, located at a 270 kb region, including four nsLTPs genes, and the expression levels of two nsLTPs genes were significantly upregulated in R06112 by RNA-Seq analysis.nsLTP positively mediated the resistance to BW of eggplants by VIGS.nsLTPs belong to the pathogenesis-related protein family, and some of them play a positive regulatory role in plant disease resistance.Study shows that plant resistance to Phytophthora infestans was positively regulated by StLTP10 [29].StLTPa7 participates in the early stages of resistance to BW in potatoes [30].The NtLTP4-overexpressing significantly improved the resistance to R. solanacearum by increasing the antioxidant enzyme activity, upregulating the expression of defense-related genes, and promoting the stomatal closure of Nicotiana benthamiana [31].Thus, nsLTPs were identified as the key candidate genes that may be involved in the resistance of eggplant R06112 to BW.The novel QTL promotes an in-depth understanding of the genetic mechanism of eggplant resistance to BW, and the developed tightly linked KASP markers can be used for new varieties breeding.

Means in groups
The genotype and phenotype of progeny become more similar to the recurrent parent after each backcross generation [32,33].Rhizosphere microorganisms have been recognized as the second genome of host plants, which co-evolved with their plants as a meta-organism, and the term 'holobiont' has been used to describe the inseparable relationship between them [34].In this study, the rhizospheric bacterial community of BC 2 F 1 populations was more similar to S51193 than R06112, which is in agreement with previous reports that rhizosphere bacteria are considered the second genome of the host.In addition, the bacterial α-diversity was higher in EB158 and EB327, which is consistent with the fact that the genotype of hybrid progeny is more complex than that of parents.These results suggested that the differences in bacterial communities in the eggplant rhizosphere are driven by genotypes.
Our study suggests that the abundances of Bacillus were significantly higher in the eggplant rhizosphere soil of resistant parent R06112 and the resistant progeny EB158 than in the susceptible progeny EB327 and susceptible parent S51193  niacini HRS2, Solibacillus silvestris HRS3, and Bacillus luciferensis HRS4 can activate JA-dependent ISR against R. solanacearum [18].Similarly, the combination of beneficial rhizosphere bacteria can improve the plants' ISR and immune response.These results show that introduced native Bacillus strains in the rhizosphere of eggplant can be used to control BW under greenhouse conditions.These findings are in agreement with previous reports that the enrichment of rhizosphere-protective microbiota promotes the inhibition of BW [19,35].In addition, Kwak et al. [19] claimed that BW-resistant tomatoes can recruit beneficial bacterial allies to protect themselves from R. solanacearum infection.Present studies reported that plants regulate rhizosphere microbiota to establish disease inhibition [19,39].However, how the QTL in disease-resistant varieties affects rhizosphere microbiota is largely unknown.Here, we first demonstrated that the QTL in resistant eggplant greatly modified the bacterial community in the rhizosphere, which jointly confers resistance to R. solanacearum (Fig. 7).Our research provides insights into the heritability of R. solanacearum-resistant rhizobacteria from resistant parent to progeny is attributed to QTL.In addition, the results indicate a potential for utilizing QTL-driven beneficial microbiota taxa for disease control.The EBWR10 will be crucial for breeding eggplant with broad-spectrum resistance to BW.Also, the Bacillus isolated in our research has good application prospects in the control of BW and promotes plant growth in eggplant and tomato plants.Resistant cultivar breeding and the rhizosphere microecological balance are the most effective and eco-friendly in controlling bacterial wilt.Future investigations are needed to (i) elucidate the function of candidate genes, (ii) identify the f luctuation of bacteria community structure in the rhizosphere with CRISPR/Cas9/sgRNA-mediated targeted gene modification, and (iii) clarify SynCom determinants that prime plant immunity.

Conclusions
The QTL in R06112 localized at 270 kb region on chromosome 10, namely EBWR10, and nsLTPs were identified as the key candidate genes controlling BW resistance.In addition, EBWR10 significantly affects the rhizosphere bacterial community and fosters the recruitment of Bacillus in the rhizosphere.The designed SynCom comprising three isolated strains could suppress disease symptoms and activate ISR and plant immune responses against R. solanacearum infection.The results of this study indicate the potential for designing microbiota taxa and microbiome-based breeding to improve plant resistance and production.The results also support the theory that the genetic basis of disease resistance assumes the hologenome of the plant and its microbial counterparts are important components of plant defense.

Plant materials
Two inbred eggplant lines, R06112 and S51193, were created and propagated in our lab (Fig. S1A and B, see online supplementary material).The S51193 is highly susceptible to BW (Fig. S1D and E, see online supplementary material), whereas R06112 is highly resistant (Fig. S1F and G, see online supplementary material).

Bacterial strains
The four R. solanacearum strains used in this study-GMI1000, KJ913688, Sm-DgHm-00-2, and Sm-Sg-08-2-belong to phylotype I (Table S1, see online supplementary material).They were chosen according to their degree of aggressiveness on eggplants, and the sequevars 15, 34, and 44 were predominant in Guangdong [40].All strains are highly aggressive on the susceptible parent S51193.The strains were cultured in Petri plates containing Kelman's triphenyl tetrazolium chloride (TTC) agar medium.The inoculated plates were incubated at 30 • C for 48 h.Colonies of R. solanacearum presenting pink-reddish pigmentation were inoculated in the f lasks containing nutrient broth (NB) medium.The f lasks were incubated at 30 • C for two days.Afterward, bacterial cells were recovered by centrifuging culture media at 4000 × g for 10 min.The pellet containing bacterial cells was suspended in autoclaved distilled water.The bacterial population was adjusted to 10 8 CFU/ml by spectrophotometer.

Genetic population construction
The non-segregating population (F 1 ) was created by crossing S51193 (female parent, Ps) and R06112 (pollen donor, P r ) (Fig. S1C, see online supplementary material).Similarly, the F 2 progenies (Fig. S1H, see online supplementary material), BC 1 P s , and BC 1 P r were obtained by self-pollinating F 1 individuals and backcrossing polymorphic efficacy of the designed primers.The polymorphic markers were used on the basis of this preliminary PCR analysis to screen the bulks and backcross population.

RNA-Seq and virus-induced gene silencing assays of the predicted genes in the QTL region
The roots of S51193 and R06112 treated plants were harvested at 6 h post-inoculation (hpi) and primarily used for RNA-Seq analysis.The RNA samples were sequenced on an Illumina Hi-Seq 2500 platform, and the downstream analyses were performed on the BMK Cloud (www.biocloud.net)at Biomarker Technologies Corporation (Beijing, China).The genes with a fold-change ≥2 and a false discovery rate (FDR) ≤0.05 were identified as DEGs.Virusinduced gene silencing assays were performed using the tobacco rattle virus (TRV) according to You et al. [44].

Rhizosphere soil sampling
The resistant cultivar R06112 (with the QTL), susceptible cultivar S51193 (without the QTL), and the individuals from the BC 2 P s population with the QTL (resistant individuals EB158-94, hereinafter referred to as EB158) or without the QTL (susceptible individuals EB327-77, hereinafter referred to as EB327) were selected by KASP markers, and resistance phenotype (Fig. 1D) were used to analyse the inf luence of BW-resistant QTL on the rhizosphere bacterial communities.Plants were grown in the field according to a randomized complete block design in Zhongluotan (23 • 23 N, 113 • 26 E), Guangzhou City, Guangdong Province, China.Each line consisted of three replicated blocks, with each block measuring 10 m × 8.7 m.The soil type was loam soil.Soil physicochemical conditions were the following: pH, 6.20; organic matter, 3.04%; total N, 0.76 g/kg; total P, 1.2 g/kg; total K, 8.37 g/kg.The same agricultural management practices were used for all the experimental fields.The application of any agrochemicals, such as pesticides, herbicides, or chemical fertilizers was not performed.
Soils from the rhizosphere of the plants were sampled at the time of early fruit formation.For that purpose, the soil adhering to the roots was collected by vigorously shaking.Afterward, a camel hair brush was used to remove the soil from the roots.The soil was collected in sterilized bags.The soil from the roots of ten replicate plants was pooled.

DNA extraction and sequence analysis of soil samples
MP DNA Isolation Kit (MO BIO Laboratories, Carlsbad, CA, USA) was used for total DNA extraction from 0.5 g soil according to the instructions for use.A universal primer (515F: 5 -GTGCCAGCMGCCGCGGTAA-3 ; 806R:5 -GGACTACHVGGGTWTCT AAT-3 ) was used to amplify the bacterial 16S rRNA gene.Sequencing libraries were constructed by TruSeq ® DNA PCR-Free Sample Preparation Kit (Illumina) by the instructions.After quality evaluation, the libraries were deep sequenced at Novogene Co., Ltd (Beijing, China) on an Illumina NovaSeq platform, and 250 bp paired-end reads were generated.
The high-quality 16S rRNA sequences were filtered and used for analyses.Standalone BLASTN analysis against a SILVA 16S rRNA gene database was conducted on sequences that removed the barcode regions and primer along with chimeric sequences by ChimeraSlayer software.Sequences with ≥97% similarity were designated to the same OTUs.The multiple sequence alignment was used to investigate the phylogenetic relationship of different OTUs and the difference of the dominant species between samples performed by the MUSCLE software (Version 3.8.31,http://www.drive5.com/muscle/).QIIME (Version 1.7.0) was used to calculate Alpha diversity (α-diversity), including Shannon and Chao1.R software (Version 2.15.3) was used to show α-diversity.QIIME software (Version 1.9.1) was used to calculate the Beta diversity (β-diversity) of the rhizospheric samples.The WGCNA package, stat packages, and ggplot2 package in R software (Version 2.15.3) were used for Principal Coordinate Analysis (PCoA) analysis.QIIME software (Version 1.9.1) was used for the Unweighted Pair-group Method with Arithmetic Means (UPGMA) Clustering analysis.

Isolation and evaluation of antagonistic bacteria
The biocontrol strains were isolated from the rhizosphere soils of EB158 individuals.Soil samples were homogenized into sterile distilled water at 150 rpm for 15 min.Soil suspensions with serial dilutions concentrations were spread on Luria broth (LB) medium and incubated at 30 • C for 24 h, and suspected colonies of bacteria were selected.

The antagonistic ability of isolates against R. solanacearum in vitro
The purified clones have been identified by antagonistic activity against R. solanacearum GMI1000 on the plate to identify antagonistic response by dual culture method [45].A total of 10 μL suspension of each isolate (OD600 = 1.0) was dripped on the R. solanacearum-inoculated plates, and the plates were incubated at 30 • C, and the inhibition zone was investigated after 48 hours.

Identification of the isolated strains
The identification of antagonistic strains against R. solanacearum was performed by 16S rRNA gene sequence and Average Nucleotide ldentity (ANI) using BLAST and aligned against sequences of reference strains in the NCBI GenBank database.Molecular Evolutionary Genetics Analysis (MEGA) software version 5.0 was used to construct phylogenetic trees by the maximum likelihood method.

Evaluation of BW suppression by the synthetic consortium
To conduct the SynCom (composed of isolated strains) treatment in a pot experiment, the final OD600 of mixed suspension culture was adjusted to 1.0.The susceptible S51193 plants were infected with R. solanacearum (a mixture of four R. solanacearum strains described in Table S1 (see online supplementary material), the bacterial population was adjusted to 10 8 CFU/ml) by irrigating roots, as mentioned above.The plants were collected at 48 hpi, and the roots were cleaned with sterile water.Secondary messengers (NO, O 2 − , H 2 O 2 ) and Defense-related enzyme (CAT, PPO, PAL) activity were measured by commercial chemical assay kits (Nanjing Jiancheng Bioengineering Institute, Nanjing, China).Phytohormone levels were measured according to Gong et al. [38].The gene-specific primers used for real-time reverse transcription-PCR (qRT-PCR) to investigate defense signaling marker genes in eggplant are listed in Table S3-S4(see online supplementary material).Triplicate qRT-PCR reactions were conducted for samples.The 2 − Ct method was used for the analysis of the relative gene expression data [46].

Statistical analysis
Genome Sequence Archive [47] in the National Genomics Data Center, China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences was used to deposit the raw sequence data (GSA: CRA008448, CRA009725) [48], which are publicly accessible at https://ngdc.cncb.ac.cn/gsa.All data were presented as mean ± standard deviation (SD).One-way analysis of variance (ANOVA) in SPSS software (SPSS, Chicago, IL, USA) was used for statistical analysis.Separations were conducted by Duncan's multiple-range tests.Differences at P < 0.01 were regarded as statistically significant.

Figure 1 .
Figure 1.Identification of genetic region(s) in R06112 associated with resistance to BW.A and B: bulked segregant analysis (BSA) (A, (SNP index) of the S-and R-pools; B, G'Value of the R-and S-pools.The SMEL3Ch01-12 indicates the 12 eggplant chromosomes.The red line represents the association threshold).C-D: Further fine mapping with BC 1 F 1 -BC 3 F 1 plants by KASP markers and BW resistance phenotype delimited EBWR10 locus into 270 kb genomic region including 20 genes.E: The expression levels of genes predicted in the QTL region in R06112 and S51193 by RNA-Seq analysis.RRt-6 h, RRt-0 h: Root of resistant cultivar R06112 infected with Ralstonia solanacearum for 6 h, and without R. solanacearum infection, respectively; SRt-6 h, SRt-0 h: Root of susceptible cultivar S55193 infected with R. solanacearum for 6 h, and without R. solanacearum infection, respectively.The numbers represent different expression levels of the genes.

Figure 2 .
Figure 2. The relative abundance of the most dominant bacterial phyla (A) and genera (B) in the eggplant rhizosphere.C: PCoA of eggplant rhizosphere bacterial community of R06112, S51193, EB158, and EB327, respectively.D: Clustering analysis of Bray-Curtis similarity coefficients for bacterial communities based on OTU abundance.

Figure 5 .
Figure 5. Disease symptoms (A), disease incidence (B), disease index (C), and the concentration of JA (D) and SA (E) of SynCom on eggplant plants infected with Ralstonia solanacearum at 48 hpi.The standard deviation for three independent replicates is represented by error bars.Significant differences between treatments are represented by different letters (P < 0.01).SynCom mixture of three Bacillus spp.strains.

Figure 6 .
Figure 6.The expression levels of SA (A) and JA (B) defense signaling marker genes in eggplants infected with Ralstonia solanacearum or/and SynCom at 48 hpi by qRT-PCR analysis.The standard deviation for three independent replicates is represented by error bars.Significant differences between treatments are represented by different letters (P < 0.01).SynCom mixture of three Bacillus spp.strains.

Figure 7 .
Figure 7.The proposed mechanisms of defense response of eggplant R06112 resistance to Ralstonia solanacearum.

Means in groups EB327 S51193 -0.01 -0.005 0 0.005 0.01 0.015 Difference between groups 95% confidence intervals
. Many plant-associated Bacillus isolates are reported naturally occurring -, NO, and H 2 O 2 are involved in the regulation of multiple signaling pathways and regulate plant defense responses.Phytohormones are vital components of multiple pathways that cesB gene in B.cereus PR-3.In summary, A synthetic community comprising these three strains displays significant disease resistance against R. solanacearum in pot experiments.The SynCom activated SA-and JA-dependent ISR against R. solanacearum in eggplant and tomato plants.JA and SA play an important role in systemic resistance and interactions between plants and microorganisms.A previous study showed that the designed SynCom comprising Brevibacterium frigoritolerans HRS1, Bacillus